6,384 research outputs found

    Information actors beyond modernity and coloniality in times of climate change:A comparative design ethnography on the making of monitors for sustainable futures in Curaçao and Amsterdam, between 2019-2022

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    In his dissertation, Mr. Goilo developed a cutting-edge theoretical framework for an Anthropology of Information. This study compares information in the context of modernity in Amsterdam and coloniality in Curaçao through the making process of monitors and develops five ways to understand how information can act towards sustainable futures. The research also discusses how the two contexts, that is modernity and coloniality, have been in informational symbiosis for centuries which is producing negative informational side effects within the age of the Anthropocene. By exploring the modernity-coloniality symbiosis of information, the author explains how scholars, policymakers, and data-analysts can act through historical and structural roots of contemporary global inequities related to the production and distribution of information. Ultimately, the five theses propose conditions towards the collective production of knowledge towards a more sustainable planet

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    The Application of Data Analytics Technologies for the Predictive Maintenance of Industrial Facilities in Internet of Things (IoT) Environments

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    In industrial production environments, the maintenance of equipment has a decisive influence on costs and on the plannability of production capacities. In particular, unplanned failures during production times cause high costs, unplanned downtimes and possibly additional collateral damage. Predictive Maintenance starts here and tries to predict a possible failure and its cause so early that its prevention can be prepared and carried out in time. In order to be able to predict malfunctions and failures, the industrial plant with its characteristics, as well as wear and ageing processes, must be modelled. Such modelling can be done by replicating its physical properties. However, this is very complex and requires enormous expert knowledge about the plant and about wear and ageing processes of each individual component. Neural networks and machine learning make it possible to train such models using data and offer an alternative, especially when very complex and non-linear behaviour is evident. In order for models to make predictions, as much data as possible about the condition of a plant and its environment and production planning data is needed. In Industrial Internet of Things (IIoT) environments, the amount of available data is constantly increasing. Intelligent sensors and highly interconnected production facilities produce a steady stream of data. The sheer volume of data, but also the steady stream in which data is transmitted, place high demands on the data processing systems. If a participating system wants to perform live analyses on the incoming data streams, it must be able to process the incoming data at least as fast as the continuous data stream delivers it. If this is not the case, the system falls further and further behind in processing and thus in its analyses. This also applies to Predictive Maintenance systems, especially if they use complex and computationally intensive machine learning models. If sufficiently scalable hardware resources are available, this may not be a problem at first. However, if this is not the case or if the processing takes place on decentralised units with limited hardware resources (e.g. edge devices), the runtime behaviour and resource requirements of the type of neural network used can become an important criterion. This thesis addresses Predictive Maintenance systems in IIoT environments using neural networks and Deep Learning, where the runtime behaviour and the resource requirements are relevant. The question is whether it is possible to achieve better runtimes with similarly result quality using a new type of neural network. The focus is on reducing the complexity of the network and improving its parallelisability. Inspired by projects in which complexity was distributed to less complex neural subnetworks by upstream measures, two hypotheses presented in this thesis emerged: a) the distribution of complexity into simpler subnetworks leads to faster processing overall, despite the overhead this creates, and b) if a neural cell has a deeper internal structure, this leads to a less complex network. Within the framework of a qualitative study, an overall impression of Predictive Maintenance applications in IIoT environments using neural networks was developed. Based on the findings, a novel model layout was developed named Sliced Long Short-Term Memory Neural Network (SlicedLSTM). The SlicedLSTM implements the assumptions made in the aforementioned hypotheses in its inner model architecture. Within the framework of a quantitative study, the runtime behaviour of the SlicedLSTM was compared with that of a reference model in the form of laboratory tests. The study uses synthetically generated data from a NASA project to predict failures of modules of aircraft gas turbines. The dataset contains 1,414 multivariate time series with 104,897 samples of test data and 160,360 samples of training data. As a result, it could be proven for the specific application and the data used that the SlicedLSTM delivers faster processing times with similar result accuracy and thus clearly outperforms the reference model in this respect. The hypotheses about the influence of complexity in the internal structure of the neuronal cells were confirmed by the study carried out in the context of this thesis

    Ethnographies of Collaborative Economies across Europe: Understanding Sharing and Caring

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    "Sharing economy" and "collaborative economy" refer to a proliferation of initiatives, business models, digital platforms and forms of work that characterise contemporary life: from community-led initiatives and activist campaigns, to the impact of global sharing platforms in contexts such as network hospitality, transportation, etc. Sharing the common lens of ethnographic methods, this book presents in-depth examinations of collaborative economy phenomena. The book combines qualitative research and ethnographic methodology with a range of different collaborative economy case studies and topics across Europe. It uniquely offers a truly interdisciplinary approach. It emerges from a unique, long-term, multinational, cross-European collaboration between researchers from various disciplines (e.g., sociology, anthropology, geography, business studies, law, computing, information systems), career stages, and epistemological backgrounds, brought together by a shared research interest in the collaborative economy. This book is a further contribution to the in-depth qualitative understanding of the complexities of the collaborative economy phenomenon. These rich accounts contribute to the painting of a complex landscape that spans several countries and regions, and diverse political, cultural, and organisational backdrops. This book also offers important reflections on the role of ethnographic researchers, and on their stance and outlook, that are of paramount interest across the disciplines involved in collaborative economy research

    Cultivating Virtue: A study into education and the political theories in classical Athens

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    This thesis is concerned with understanding the relevance of education to good leadership within the political writings of fifth and fourth century Athenian thinkers. I ask why education became such a universal component to the works of post-Socratic thinkers. What specifically were the lessons or skills that were seen to be so important to competent ruling and how might a society be designed in order to cultivate those lessons within its leadership? To address these questions, the thesis will assess the works of Xenophon, with particular attention given to the Cyropaedia, Isocrates and Plato’s Republic and Laws. I propose that as a result of Athenian theatre and the rise of sophist teachings, especially in the fifth century, education came to be acknowledged as important to democracy and leadership. As a result, by the close of the fifth century, Athenian thinkers considered how education could be used to create good and even idealised leadership. I argue that for all our sources, leaders needed actively to learn the needs of their society and how to control their own desires and ambitions in order to rule in the best interests of all. I show that while different thinkers approach this idea from slightly different positions or by using different terminology, they maintain this common notion that education was relevant to leadership. It is within the question of how best to cultivate these lessons in society, that our sources begin to demonstrate more difference. Yet I will demonstrate how all our thinkers design meritocracies based around one’s mastery of moderation and social awareness. They all establish hierarchies, while also attempting to avoid forceful ruling. Ultimately, I will show how they all create societies obsessed with the cultivation of education, so as to ensure future leaders can judge what is for the benefit of all members of society

    Dialogues concerning Natural Politics: A Modern Philosophical Dialogue about Policymaker Ignorance

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    How should we conceive of policymakers for the purposes of political analysis? In particular, if we wish to explain and predict political decisions and their consequences, if we wish to ensure that political action is as effective as it can be, how should we think of policymakers? Should we think of them as they are commonly conceived in traditional political analysis, i.e., as uniquely knowledgeable and as either altruistic (i.e., as motivated to realize goals associated with their constituents’ interests) or knavish (i.e., as motivated to realize goals associated with their own personal interests), or should we treat them as possibly ignorant with respect to their political tasks? It is always an open question whether policymakers possess the knowledge required to realize some policy objective. It should never be assumed a priori that policymaker knowledge is adequate to the policy tasks with which policymakers are charged. Politicians need knowledge concerning the causes of social phenomena adequate to control events sufficiently well to ensure the success of their policies. No argument has ever been offered for the standard, if only implicit, assumption that policymakers, somehow automatically, possess this knowledge. In many contexts, there is no reason to believe that policymakers possess or can acquire this knowledge. Indeed, a bit of reflection reveals how unlikely it is that and how rare the circumstances must be in which policymakers meet this condition, which political philosophers, theorists, economists, and other political thinkers have traditionally assumed as a matter of course. The main purpose of the book is to encourage a conversation among scholars and students of political inquiry (in philosophy and political theory, political science, economics and political economy) concerning the best way to conceive of policymakers for the purposes of such inquiry. The book defends an alternative, more realistic, method of political analysis. The book argues against the false assumption that policymakers are epistemically privileged. The book presents and defends the alternative assumption that, with respect to the knowledge required to discharge their political tasks effectively, policymakers are at least as ignorant as constituents. The book further argues that whether policymakers are altruistic or knavish is, in the first instance, a function of the nature and extent of their ignorance with regard to constituent-minded policy goals. Policymakers who possess the knowledge required to be effectively altruistic are more likely to be altruistic, other things the same, than policymakers who are ignorant of the knowledge that successful altruism requires. This being said, my goal is more to leave readers thinking about and inclined to debate these profound issues than to prescribe a particular methodological conclusion (even less to advocate a particular political conclusion). The book is a heuristic for spurring further conversation. It makes of readers fellow interlocutors partnered with the characters (and the author!) of the dialogue. The vehicle for this analysis is a conversation between four friends, philosophy graduate students, with different interests, different levels and kinds of experience, and different political preferences. The four friends consider how politicians should be conceived for the purposes of analyzing political decision-making and its consequences. In his famous Dialogues concerning Natural Religion, David Hume concluded that the assumption of an all-knowing and all-powerful God was neither necessary nor sufficient to explain natural phenomena. Dialogues concerning Natural Politics does for social science what Hume did for natural science. Both books undermine the assumption that some epistemically privileged being – God in the case of natural phenomena and God-like politicians in the case of social phenomena – must be invoked to explain relevant phenomena

    The Forward Physics Facility at the High-Luminosity LHC

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